Main Investigator: Prof. Ing. Kenneth P. Camilleri, Centre for Biomedical Cybernetics, Department of Systems and Control Engineering
Main Investigator: Prof. Ing. Tracey Camilleri, Centre for Biomedical Cybernetics, Department of Systems and Control Engineering
Main Investigator: Prof. Ing. Marvin Bugeja, Department of Systems and Control Engineering
Main Investigator: Prof. Ing. Simon Fabri, Department of Systems and Control Engineering
Research Support Officer: Dr Natasha Padfield, Centre for Biomedical Cybernetics
External Collaborating Partner: Dr Andrei Agius Anastasi, Karen Grech Hospital
Externally funded: Transdisciplinary Research and Knowledge Exchange Complex (2021-2024)
Summary:
In this project we seek to: (a) integrate a BCI signal to the dynamic model of a smart wheelchair; (b) develop new methods permitting multi-dimensional control signal integration to include, e.g., speed control and direction control; (c) estimate signal integration parameters by reinforcement learning to be tuned by practice; and (d) to explore more intuitive mental states, such as thought speech. Combining an intuitive mental state command with a paradigm of continuous BCI control would lead to a more natural brain-machine interaction resembling embodied control, making this technology more viable for people with motor impairment. The project team is made up of experts in BCIs, experts in mobile robots, and a medical doctor specialising in rehabilitation medicine. The BCI experts will contribute to the development of a BCI platform and to the investigation of alternative BCI mental states; the robot experts will contribute to the development of the physical wheelchair model and the integration models; and the medical doctor will contribute end-user advice and recruitment.
